Senior Machine Learning Engineer

Experience: 10+ Years

Location: Bangalore

Employment Type: Full-Time

Work Mode: [Hybrid]

Job Summary

We are looking for an experienced Senior Machine Learning Engineer with 10+ years of professional experience in Machine Learning Engineering, Software Engineering with a strong ML focus, or a similar role.

The ideal candidate will combine strong software engineering fundamentals with deep expertise in machine learning, data processing, model development, and production-grade ML solutions. The role requires hands-on experience with Python, PyTorch, Scikit-learn, ML algorithms, feature engineering, model evaluation, hyperparameter tuning, SQL/NoSQL databases, and large-scale data processing.

The successful candidate should be able to translate complex business and technical problems into practical, scalable ML solutions and communicate effectively with both technical and non-technical stakeholders.

Key Responsibilities

Machine Learning Engineering

- Design, develop, implement, and maintain machine learning models and solutions for complex business problems.
- Apply strong theoretical and practical knowledge of machine learning algorithms to real-world use cases.
- Select appropriate algorithms, approaches, and techniques based on business and technical requirements.
- Perform feature engineering, model training, validation, evaluation, and optimization.
- Define and analyze appropriate model evaluation metrics.
- Perform hyperparameter tuning and model optimization.
- Collaborate with engineering and data teams to transition ML models into production-ready solutions.

Software Engineering

- Develop clean, efficient, scalable, production-grade, and well-documented Python code.
- Apply strong software engineering principles to ML systems and applications.
- Design reusable and maintainable software components using appropriate design patterns and object-oriented programming principles.
- Apply strong knowledge of:
- Data Structures
- Algorithms
- Object-Oriented Programming
- Software Design Patterns
- Distributed Systems

- Ensure solutions are scalable, reliable, maintainable, and efficient.





Data Engineering & Data Handling

- Work with large and complex datasets to support machine learning initiatives.
- Develop data processing and transformation workflows required for ML model development.
- Work with both SQL and NoSQL databases.
- Apply knowledge of data warehousing concepts and large-scale data processing.
- Perform data analysis, preparation, validation, and feature extraction.
- Collaborate with data engineering teams to ensure availability and quality of data required for ML applications.

ML Frameworks

- Develop machine learning solutions using frameworks and libraries including:
- PyTorch
- Scikit-learn

- Evaluate and select appropriate frameworks and techniques based on the requirements of the solution.
- Maintain and optimize ML implementations for performance and scalability.

Problem Solving & Innovation

- Analyze complex technical and business problems and develop pragmatic, scalable solutions.
- Evaluate different approaches and make data-driven technical decisions.
- Identify opportunities to improve existing ML models, processes, and engineering practices.
- Troubleshoot model, data, and application-related issues.
- Balance technical excellence with practical business requirements and delivery timelines.

Collaboration & Communication

- Work closely with Data Scientists, ML Engineers, Software Engineers, Data Engineers, Product Managers, and other stakeholders.
- Translate business requirements into technical and ML solutions.
- Explain complex machine learning and technical concepts clearly to technical and non-technical audiences.
- Prepare technical documentation and communicate solution approaches, assumptions, limitations, and outcomes.




- Collaborate effectively across teams to deliver high-quality solutions.

Required Qualifications

Education

- Masters degree in:
- Computer Science
- Machine Learning
- Data Science
- Electrical Engineering
- or another related quantitative field.

Experience

- 10+ years of professional experience in:
- Machine Learning Engineering
- Software Engineering with a strong ML focus
- or a closely related role.

Programming

Must Have:

- Strong proficiency in Python.
- Experience writing:
- Production-grade code
- Clean and maintainable code
- Efficient code
- Well-documented code

Good to Have:

- Experience with additional programming languages such as:
- Java
- Go
- C++

Software Engineering Fundamentals

Strong understanding of:

- Software Design Patterns
- Data Structures
- Algorithms
- Object-Oriented Programming
- Distributed Systems
- Software Development Best Practices

Machine Learning

Strong theoretical and practical knowledge of:

- Machine Learning Algorithms
- Supervised Learning
- Unsupervised Learning
- Feature Engineering
- Model Evaluation
- Evaluation Metrics
- Hyperparameter Tuning
- Model Optimization

ML Frameworks

- PyTorch
- Scikit-learn

Data

- Strong experience with SQL.
- Experience with NoSQL databases.
- Understanding of data warehousing concepts.
- Experience processing and working with large datasets.

Good-to-Have Skills

- Java
- Go
- C++
- Experience with distributed ML systems.
- Experience taking ML models from development through production.
- Exposure to ML pipelines and production ML environments.
- Experience with cloud-based ML platforms.
- Knowledge of MLOps practices.

Key Competencies

- Solid analytical and problem-solving skills.
- Pragmatic approach to solving complex problems.
- Strong software engineering mindset.
- Ability to work independently as well as collaboratively.
- Strong verbal and written communication.
- Ability to explain complex technical concepts to diverse audiences.
- Strong ownership and execution capabilities.
- Ability to work effectively in a fast-paced technical environment.

📌 Senior Machine Learning Engineer (Bengaluru)
🏢 Anlage Infotech
📍 Bengaluru